In existing industrial monitoring systems, relevant data is generally stored in a conventional relational database, e.g. MSSQL, Oracle or Mysql. These relational databases are good at processing the storage and accessing of data having complex logical relationships. These data having complex logical relationships are stored in a table in a manner of logical combination, based on the principal of minimum redundancy; when data is accessed and complex data analysis is performed, it may be necessary to subject multiple tables to relational query.
However, as industrial monitoring systems increase in scale and complexity while applications become more demand-based at a deep level, large amounts of sample data need to be added to databases, to be extracted by upper-level applications and used for data mining, scientific calculations, and the generation of reports and images, etc. It is very time-consuming to store such colossal data amounts one item at a time in different relational database report forms, and it is not easy to extract these data from the different relational database report forms.
On this basis, following industrial networking and real-time requirements, certain real-time database systems for industrial production have emerged, such as industrial SQL from the company Wonderware, PL from the company OSlsoft, and InfoPlus.2.1. from the company ASPEN, etc. However, these real-time database systems are too expensive for some small-to-medium sized enterprises.